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An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes

Blanco Capurro, Juan Ignacio et al · Oxford University Press · 2018

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Unraveling the structure of lectin-carbohydrate complexes is vital for understanding key biological recognition processes and development of glycomimetic drugs. Molecular Docking application to predict them is challenging due to their low affinity, hydrophilic nature and ligand conformational diversity. In the last decade several strategies, such as the inclusion of glycan conformation specific scoring functions or our developed solvent-site biased method, have improved carbohydrate docking performance but significant challenges remain, in particular, those related to receptor conformational diversity. In the present work we have analyzed conventional and solvent-site biased autodock4 performance concerning receptor conformational diversity as derived from different crystal structures (apo and holo), Molecular Dynamics snapshots and Homology-based models, for 14 different lectin-monosaccharide complexes. Our results show that both conventional and biased docking yield accurate lectin-monosaccharide complexes, starting from either apo or homology-based structures, even when only moderate (45%) sequence identity templates are available. An essential element for success is a proper combination of a middle-sized (10-100 structures) conformational ensemble, derived either from Molecular dynamics or multiple homology model building. Consistent with our previous works, results show that solvent-site biased methods improve overall performance, but that results are still highly system dependent. Finally, our results also show that docking can select the correct receptor structure within the ensemble, underscoring the relevance of joint evaluation of both ligand pose and receptor conformation. Fil: Blanco Capurro, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Di Paola, Matías Ezequiel. Universidad de Buenos Aires; Argentina

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APA 7

Blanco Capurro, J. I. E. A. (2018). An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes. http://hdl.handle.net/11336/97997

MLA

Blanco Capurro, Juan Ignacio et al. "An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes." 2018. http://hdl.handle.net/11336/97997.

Chicago

Blanco Capurro, Juan Ignacio et al. 2018. "An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes.". http://hdl.handle.net/11336/97997.

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Blanco Capurro, J. I. E. A. 2018, An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes, Oxford University Press, available at: http://hdl.handle.net/11336/97997 [Accessed 8 Aug. 2026].

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Titolo
An efficient use of X-ray information, homology modeling, molecular dynamics and knowledge-based docking techniques to predict protein-monosaccharide complexes
Autore / collaboratori
Blanco Capurro, Juan Ignacio et al
Editore
Oxford University Press
Anno di pubblicazione
2018
ISSN
0959-6658
ISSN
0959-6658
Lingua
Inglés

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